Mohammadi and Saniee Abadeh in [1]} first presented the idea of dimension reduction using evolutionary algorithms like ABC, then in [2]} proposed a new steganalysis method named IFAB, which helps steganalysis to enhance the performance of distinguishing stego images from the cover images. Authors adopted a wrapper-based feature selection technique by customizing the original ABC into the discrete ABC algorithm. ABC selects the feature subsets, and a classifier is employed to evaluate every feature subset generated by the algorithm. According to the IFAB algorithm for feature selection, the process of feature selection solves the problem of CoD by leveraging employed bees, onlooker bees and a scout bee.
